Update app.py

app.py

@@ -3,30 +3,59 @@ import os
 import gradio as gr
 from transformers import pipeline
 import whisper
+import random
+import time
 
 def get_audio(url):
     try:
-        # Configure yt-dlp options
+        # Configure yt-dlp options without browser cookies
         ydl_opts = {
-            'format': 'bestaudio/best',  # Choose best quality audio
+            'format': 'bestaudio/best',
             'postprocessors': [{
                 'key': 'FFmpegExtractAudio',
                 'preferredcodec': 'mp3',
                 'preferredquality': '192',
             }],
-            'outtmpl': 'audio_download.%(ext)s',  # Output template
-            'quiet': True,  # Less output
-            'no_warnings': True  # No warnings
+            'outtmpl': 'audio_download.%(ext)s',
+            'quiet': True,
+            'no_warnings': True,
+            # Add basic user agent
+            'user_agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36',
+            # Add other options to help avoid restrictions
+            'extractor_args': {'youtube': {
+                'player_client': ['android', 'web'],
+                'skip': ['dash', 'hls']
+            }},
+            # Add network options
+            'socket_timeout': 30,
+            'retries': 3,
         }
         
+        # Add small delay to avoid rate limiting
+        time.sleep(random.uniform(1, 2))
+        
         # Download the audio
         with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+            info = ydl.extract_info(url, download=False)
+            duration = info.get('duration', 0)
+            
+            # Check video duration (optional)
+            if duration > 1800:  # 30 minutes
+                raise gr.Error("Video is too long. Please use videos under 30 minutes.")
+                
             ydl.download([url])
             
-        return 'audio_download.mp3'  # Return the filename
+        return 'audio_download.mp3'
         
     except Exception as e:
-        raise gr.Error(f"Error downloading audio: {str(e)}")
+        if 'Sign in to confirm' in str(e):
+            raise gr.Error("This video requires age verification. Please try a different video.")
+        elif 'Private video' in str(e):
+            raise gr.Error("This video is private. Please try a public video.")
+        elif 'Video unavailable' in str(e):
+            raise gr.Error("This video is unavailable. Please check the URL and try again.")
+        else:
+            raise gr.Error(f"Error downloading audio: {str(e)}")
 
 # Load models
 model = whisper.load_model("base")
@@ -34,6 +63,10 @@ summarizer = pipeline("summarization")
 
 def get_text(url):
     try:
+        # Validate URL
+        if not url.startswith('https://www.youtube.com/') and not url.startswith('https://youtu.be/'):
+            raise gr.Error("Please enter a valid YouTube URL")
+            
         audio_file = get_audio(url)
         result = model.transcribe(audio_file)
         
@@ -50,29 +83,57 @@ def get_text(url):
 def get_summary(url):
     try:
         article = get_text(url)
-        summary = summarizer(article)
-        return summary[0]['summary_text']
+        if isinstance(article, str) and article.startswith("Error:"):
+            return article
+            
+        # Handle empty or short text
+        if not article or len(article.split()) < 30:
+            return "Text too short to summarize. Please try a longer video."
+            
+        # Split long text into chunks
+        max_chunk_length = 1000
+        chunks = [article[i:i+max_chunk_length] for i in range(0, len(article), max_chunk_length)]
+        summaries = []
+        
+        for chunk in chunks:
+            summary = summarizer(chunk, max_length=130, min_length=30, do_sample=False)
+            summaries.append(summary[0]['summary_text'])
+            
+        return " ".join(summaries)
     except Exception as e:
         return f"Error: {str(e)}"
 
 # Create Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("<h1><center>YouTube Video Transcription with OpenAI's Whisper</center></h1>")
-    gr.Markdown("<center>Enter the link of any YouTube video to get the transcription and summary.</center>")
+    gr.Markdown("<center>Enter the link of any YouTube video to get the transcription and summary. Please use videos under 30 minutes in length.</center>")
     
     with gr.Tab('Get the transcription of any Youtube video'):
         with gr.Row():
-            input_text_1 = gr.Textbox(placeholder='Enter the Youtube video URL', label='URL')
-            output_text_1 = gr.Textbox(placeholder='Transcription of the video', label='Transcription')
+            input_text_1 = gr.Textbox(
+                placeholder='Enter the Youtube video URL (e.g., https://www.youtube.com/watch?v=...)',
+                label='URL'
+            )
+            output_text_1 = gr.Textbox(
+                placeholder='Transcription of the video',
+                label='Transcription'
+            )
         result_button_1 = gr.Button('Get Transcription')
         
     with gr.Tab('Summary of Youtube video'):
         with gr.Row():
-            input_text = gr.Textbox(placeholder='Enter the Youtube video URL', label='URL')
-            output_text = gr.Textbox(placeholder='Summary text of the Youtube Video', label='Summary')
+            input_text = gr.Textbox(
+                placeholder='Enter the Youtube video URL (e.g., https://www.youtube.com/watch?v=...)',
+                label='URL'
+            )
+            output_text = gr.Textbox(
+                placeholder='Summary text of the Youtube Video',
+                label='Summary'
+            )
         result_button = gr.Button('Get Summary')
 
     result_button.click(get_summary, inputs=input_text, outputs=output_text)
     result_button_1.click(get_text, inputs=input_text_1, outputs=output_text_1)
 
+# Launch with appropriate settings
 demo.launch(debug=True)